Interpretable multitemporal liver function indicator model for prediction and risk factor analysis of drug induced liver injury.

The occurrence of liver injury during cancer treatment is extremely harmful. The risk factors for drug.induced liver injury (DILI) in the pancreatic cancer population have not been investigated. This study aims to develop and validate an interpretable decision tree (DT) model for the early prediction of DILI in pancreatic cancer patients using multitemporal clinical data and screening for related risk factors. A retrospective collection of data was conducted on 307 patients, the training set (n = 215) was used to develop the model, and the test set (n = 92) was used to evaluate the model. The classification and regression trees algorithm was employed to establish the DT model. The Shapley Additive explanations (SHAP) method was used to facilitate clinical interpretation. Model performance was assessed using AUC and the Hosmer‒Lemeshow test. The DT model exhibited superior diagnostic efficacy, the AUC values were 0.995 and 0.994 in the training and test sets, respectively. Four risk factors associated with DILI occurrence were identified: delta.albumin, delta.ALT, and post (AST: ALT), and post.GGT. The multiperiod liver function indicator.based interpretable DT model predicted DILI occurrence in the pancreatic cancer population and contributes to personalized clinical management of pancreatic cancer patients.

Comparison of the Efficacy and Safety Between Intravenous Thrombolysis, Direct Endovascular Therapy, and Bridging Therapy for Acute Basilar Artery Occlusion in Cerebral Infarction Patients.

OBJECTIVE: To compare the efficacy and safety of intravenous thrombolysis, direct endovascular therapy (EVT), and bridging therapy (BT = intravenous thrombolysis + EVT) for acute basilar artery occlusion cerebral infarction. METHODS: One hundred and fourteen patients with acute basilar artery occlusion cerebral infarctions admitted between January 2020 and August 2023 were selected. Differences in the reperfusion rate, prognosis, incidence of stroke-associated pneumonia, and mortality rate were compared among the 3 groups. RESULTS: There was no statistically significant difference in the percentage of patients who achieved successful reperfusion (86.8% vs. 84.2%) or complete reperfusion (72.1% vs. 68.4%) between the direct EVT and BT groups (both P > 0.05). There were no statistically significant differences in the rates of symptomatic intracranial hemorrhage (3.7% vs. 10.3% vs. 10.5%, P = 0.763). There were statistically significant differences in the rates of good prognosis (modified ranking scale score 0-2) (59.3% vs. 30.9% vs. 26.3%, P = 0.021), stroke-related pneumonia (29.6% vs. 66.2% vs. 36.8%, P = 0.002), and mortality (14.8% vs. 48.5% vs. 42.1%, P = 0.010) among the 3 treatment groups. According to the binary logistic regression analysis, a good prognosis was independently associated with a baseline National Institutes of Health Stroke Scale score ≤ 10 (odds ratio, 3.714; 95% confidence interval, 1.207-11.430; P = 0.022) and the incidence of stroke-associated pneumonia (odds ratio, 0.640; 95% confidence interval, 0.484-0.845; P = 0.002). CONCLUSIONS: Although there were differences in prognosis, mortality, and incidence of complications among the 3 treatment groups, after adjusting for confounding factors, prognosis was independently correlated only with the baseline NIHSS score and stroke-associated pneumonia but not with treatment methods.

Prediction of postoperative liver metastasis in pancreatic ductal adenocarcinoma based on multiparametric magnetic resonance radiomics combined with serological markers: a cohort study of machine learning.

OBJECTIVE: To construct and validate a multi-dimensional model based on multiple machine leaning algorithms to predict PCLM using multi-parameter magnetic resonance (MRI) sequences with clinical and imaging parameters. METHODS: A total of 148 PDAC retrospectively examined patients were classified as metastatic or non-metastatic based on results at 3 months after surgery. The radiomics features of the primary tumor were extracted from T2WI images, followed by dimension reduction. Then, multiple machine learning methods were used to construct models. Independent predictors were also screened using multifactor logistic regression and a nomogram was constructed in combination with the radiomics model. Area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to assess the accuracy and reliability of the nomogram. RESULTS: The diagnostic efficacy of the radiomics model in the training and test set was 0.822 and 0.803, sensitivity was 0.742 and 0.692, and specificity was 0.792 and 0.875, respectively. The diagnostic efficacy of the nomogram in the training and test set was 0.866 and 0.832. CONCLUSION: A radiomics nomogram based on machine learning improved the accuracy of predicting PCLM and may be useful for early preoperative diagnosis.

Malignant gastrointestinal neuroectodermal tumor: a case report and literature review.

Introduction and importance: A malignant gastrointestinal neuroectodermal tumor (GNET) is an extremely rare primary malignant mesenchymal tumor of the gastrointestinal tract characterized by EWSR1 gene rearrangement. An optimal systemic treatment strategy for advanced/recurrent GNET has not yet been identified. Case presentation: A 24-year-old male patient was hospitalized with abdominal pain and underwent two operations for a tumor in his small intestine. Immunohistochemistry (IHC) showed strong expression of S-100 protein and SOX 10. Fluorescence in situ hybridization analysis and next-generation sequencing analysis indicated that there were EWSR gene rearrangements and the presence of EWSR-ATP1 gene fusions, respectively. The diagnosis of GNET in the small intestine was confirmed by pathology. The young patient received the fifth-line of apatinib mesylate and the sixth-line of apatinib combined with temozolomide. The two apatinib-containing regimens showed stable disease and progression-free survival of 4.7 months and 3.1 months with single-agent apatinib or apatinib combined with temozolomide, respectively. Clinical discussion: To our best knowledge, this is the first report of malignant GNET treated with apatinib and temozolomide. Apatinib-containing regimens might has antineoplastic activity against GNET. The authors reviewed the relevant reports of previous GNET treatment, summarized the clinicopathological characteristics of GNET, and found that there are no reports of apatinib for backline treatment of GNET. Conclusion: Containing apatinib may provide an additional treatment option for patients with chemotherapy-resistant GNET tumors.

Factors correlated with excessive daytime sleepiness in patients with Parkinson's disease: A polysomnography study.

OBJECTIVE: To explore the factors correlated with excessive daytime sleepiness (EDS) in patients with Parkinson's disease (PD). METHODS: A total of 239 PD patients were divided into two groups based on the presence of EDS (Epworth Sleepiness Scale score≥10) (PD-EDS vs. PD-non-EDS). Participants underwent an extensive assessment to determine demographic features, disease severity, polysomnography characteristics, and nonmotor symptoms. RESULTS: Of the 239 patients, 56 patients (23.4%) were classified as having PD combined with EDS. Binary logistic regression analysis showed that fatigue (Fatigue Severity Scale [FSS] score ≥4) (odds ratio [OR] [95% CI] = 4.897 [2.376-10.095], p < .001) and the respiratory-related microarousal index (OR [95% CI] = 2.063 [1.085-3.923], p = .027) were independent risk factors for EDS in PD patients. A priori-determined stratified analysis showed that after adjustment for confounding factors, the association of the respiratory-related microarousal index with EDS was significant (OR = 4.404, 95% CI 1.673-11.592, p trend = .036) in patients with respiratory arousal index scores in the highest quintile compared with those with scores in the lowest quintile. CONCLUSION: Our data revealed a close association among the respiratory-related microarousal index, FSS scores, and EDS. It can be speculated that fragmented sleep and pathological abnormalities of the central nervous system resulting in changes in arousal are major influencing factors of EDS in PD.

Predicting prostate cancer in men with PSA levels of 4-10 ng/mL: MRI-based radiomics can help junior radiologists improve the diagnostic performance.

To develop MRI-based radiomics model for predicting prostate cancer (PCa) in men with prostate-specific antigen (PSA) levels of 4-10 ng/mL, to compare the performance of radiomics model and PI-RADS v2.1, and to further verify the predictive ability of radiomics model for lesions with different PI-RADS v2.1 score. 171 patients with PSA levels of 4-10 ng/mL were divided into training (n = 119) and testing (n = 52) groups. PI-RADS v2.1 score was assessed by two radiologists. All volumes of interest were segmented on T2-weighted imaging, diffusion weighted imaging, and apparent diffusion coefficient sequences, from which quantitative radiomics features were extracted. Multivariate logistic regression analysis was performed to establish radiomics model for predicting PCa. The diagnostic performance was assessed using receiver operating characteristic curve analysis. The radiomics model exhibited the best performance in predicting PCa, which was better than the performance of PI-RADS v2.1 scoring by the junior radiologist in the training group [area under the curve (AUC): 0.932 vs 0.803], testing group (AUC: 0.922 vs 0.797), and the entire cohort (AUC: 0.927 vs 0.801) (P < 0.05). The radiomics model performed well for lesions with PI-RADS v2.1 score of 3 (AUC = 0.854, sensitivity = 84.62%, specificity = 84.34%) and PI-RADS v2.1 score of 4-5 (AUC = 0.967, sensitivity = 98.11%, specificity = 86.36%) assigned by junior radiologist. The radiomics model quantitatively outperformed PI-RADS v2.1 for noninvasive prediction of PCa in men with PSA levels of 4-10 ng/mL. The model can help improve the diagnostic performance of junior radiologists and facilitate better decision-making by urologists for management of lesions with different PI-RADS v2.1 score.

Effect of cerebral small vessel disease on cognitive impairment in Parkinson's disease.

OBJECTIVES: To explore the association between cerebral small vessel disease (cSVD) and cognitive impairment (CI) in Parkinson's disease (PD). METHODS: 81 PD patients were recruited into the study from September 2018 to December 2020. The demographic characteristics and radiologic and laboratory data were collected. Cognitive assessments were carried out using the Montreal Cognitive Assessment. The association between cSVD and cognitive impairment was analyzed using univariate and binary logistic regression analysis. RESULTS: The binary logistic regression analysis showed that, after correcting for age, educational years, hyperhomocysteinemia, hypertension, and diabetes mellitus, total cSVD scores (OR 1.55, 95% CI 1.07-2.27, P = 0.02), the presence of paraventricular white matter hyperintensity (PVH) (OR 11.78, 95% CI 3.08-45.01, P < 0.001), white matter hyperintensity (WMH) (OR 7.95, 95% CI 2.28-27.79, P = 0.001), and perivascular space (PVS) (OR 6.66, 95% CI 2.08-21.40, P = 0.001) were independent risk factors for PD-CI. CONCLUSION: The presence of cSVD was associated with cognitive dysfunction in patients with PD. It may be beneficial to manage cSVD to prevent the progression of cognitive impairment in patients with PD.

Theory of mind and facial emotion recognition in adults with temporal lobe epilepsy: A meta-analysis.

Background: Mounting studies have investigated impairments in social cognitive domains (including theory of mind [ToM] and facial emotion recognition [FER] in adult patients with temporal lobe epilepsy (TLE). However, to date, inconsistent findings remain. Methods: A search of PubMed, Web of Science, and Embase databases was conducted until December 2021. Hedges g effect sizes were computed with a random-effects model. Meta-regressions were used to assess the potential confounding factors of between-study variability in effect sizes. Results: The meta-analysis included 41 studies, with a combined sample of 1,749 adult patients with TLE and 1,324 healthy controls (HCs). Relative to HCs, adult patients with TLE showed large impairments in ToM (g = -0.92) and cognitive ToM (g = -0.92), followed by medium impairments in affective ToM (g = -0.79) and FER (g = -0.77). Besides, no (statistically) significant differences were observed between the magnitude of social cognition impairment in adult with TLE who underwent and those who did not undergo epilepsy surgery. Meta-regressions exhibited that greater severity of executive functioning was associated with more severe ToM defects, and older age was associated with more severe FER defects. Conclusions: Results of this meta-analysis suggest that adult patients with TLE show differential impairments in the core aspects of social cognitive domains (including ToM and FER), which may help in planning individualized treatment with appropriate cognitive and behavioral interventions.

Social cognition in children and adolescents with epilepsy: A meta-analysis.

Many studies have investigated impairments in two key domains of social cognition (theory of mind [ToM] and facial emotion recognition [FER]) in children and adolescents with epilepsy. However, inconsistent conclusions were found. Our objective was to characterize social cognition performance of children and adolescents with epilepsy. A literature search was conducted using Web of Science, PubMed, and Embase databases. The article retrieval, screening, quality assessment (Newcastle-Ottawa-Scale), and data extraction were performed independently by two investigators. A random-effects model was used to examine estimates. The meta-analysis included 19 studies, with a combined sample of 623 children and adolescents with epilepsy (mean [SD] age, 12.13 [2.62] years; 46.1% female) and 677 healthy controls [HCs]) (mean [SD] age, 11.48 [2.71] years; 50.7% female). The results revealed that relative to HCs, children and adolescents with epilepsy exhibited deficits in ToM (g = -1.08, 95% CI [-1.38, -0.78], p < 0.001, the number of studies [k] = 13), FER (g = -0.98, 95% CI [-1.33, -0.64], p < 0.001, k = 12), and ToM subcomponents (cognitive ToM: g = -1.04, 95% CI [-1.35, -0.72], p < 0.001, k = 12] and affective ToM: g = -0.73, 95% CI [-1.12, -0.34], p < 0.001, k = 8). In addition, there were no statistically significant differences in social cognition deficits between children and adolescents with focal epilepsy and generalized epilepsy. Meta-regressions confirmed the robustness of the results. These quantitative results further deepen our understanding of the two core domains of social cognition in children and adolescents with epilepsy and may assist in the development of cognitive interventions for this patient population. Systematic review registration: https://inplasy.com/inplasy-2022-3-0011/, identifier INPLASY202230011.

Theory of Mind and Empathy in Adults With Epilepsy: A Meta-Analysis.

Mounting evidence suggests that social cognitive abilities [including theory of mind (ToM) and empathy] are impaired in adult patients with epilepsy. Although the deficits in overall ToM in epilepsy have been documented well, the effects of epilepsy on empathic ability and specific subcomponents of ToM remain unclear. The primary aim of this study was to provide the first meta-analytic integration of ToM and empathy in adult patients with epilepsy, and to decompose these constructs to clearly differentiate their distinct (cognitive ToM and affective empathy) and overlapping (affective ToM/cognitive empathy) components. This meta-analysis included 28 studies. Adult patients with temporal lobe epilepsy (TLE) and frontal lobe epilepsy (FLE) showed impairments in cognitive ToM and affective ToM/cognitive empathy compared to the healthy controls (HCs); no group differences were identified for affective empathy. Besides, cognitive ToM was impaired in adult patients with idiopathic generalized epilepsy (IGE) and focal seizures (caused by epileptogenic foci) outside the temporal and frontal lobes (extra-TLE/FLE) and no group differences were evident for affective ToM/cognitive empathy compared to the HCs. Moreover, relative to the HCs, no group differences were identified for affective empathy in adult patients with IGE. Additionally, no (statistically) significant difference was observed between the magnitude of ToM/empathy impairment in adult patients who underwent and those who did not undergo epilepsy surgery. These quantitative findings suggest differential impairment of the core aspects of social cognitive processing in adult patients with epilepsy, which may contribute to the development of structured cognitive interventions (i.e., social cognitive training) for adult patients with epilepsy.

CT-based differentiation of solid pseudopapillary neoplasm and nonfunctional neuroendocrine tumor of pancreas.

PURPOSE The purpose of this paper was to distinguish solid pseudopapillary neoplasms (SPNs) and nonfunctional neuroendocrine tumors (nf-NETs) of pancreas using univariate analysis and clinical-CT logistic regression model. METHODS Twenty-eight patients with SPNs and 46 patients with nf-NETs underwent enhanced CT examinations. Clinical data (sex, age), categorical (location, cystic degeneration, calcification, hemorrhage, and enhancement pattern), and numeric CT features (lesion long diameter, long/ short diameter ratio, tumor attenuation values and tumor/pancreas attenuation ratios at unenhanced phase [UP], arterial phase [AP], and venous phase [VP]) were recorded. The logistic regression model was constructed by stepwise forward method of binary logistic regression after univariate analysis. The corresponding operating characteristic curve (ROC) and nomogram were delineated. The area under the curve (AUC), sensitivity, and specificity of ROC were calculated. RESULTS The SPNs were observed more often in relatively young (P < .001), female (P < .001) patients. After the univariate analysis, the categorical CT features of location (P = .048), hemorrhage (P = .003), and enhancement pattern (P = .004) and the numeric CT features of lesion long diameter (P = .005), tumor/pancreasUP (P = .002), tumorAP (P < .001), and tumor/pancreasAP (P < .001) had statistical significance. The AUC (95% CI), sensitivity, and specificity of a logistic regression model composed of age, tumor/pancreasUP, and tumor/pancreasAP were 0.933 (95% CI, 0.850-0.978), 84.78%, and 92.86%. CONCLUSION The SPNs often occurred in 20- to 40-year-old female patients, were located in the body or tail of pancreas, showed hemorrhagic degeneration, heterogeneous enhancement, and were relatively larger in size compared with nf-NETs. Tumor/pancreasUP, tumorAP, and tumor/pancreasAP values of SPNs were smaller than those of nf-NETs. The clinical-CT logistic regression model and nomogram consisting of age, tumor/pancreasUP, and tumor/pancreasAP parameters helped to differentiate SPNs from nf-NETs.

Correlation Between Intracranial Carotid Artery Calcification and Prognosis of Acute Ischemic Stroke After Intravenous Thrombolysis.

Objective: To investigate the correlation between prognosis and intracranial carotid artery calcification (ICAC) in patients with acute ischemic stroke (AIS) who receive intravenous thrombolysis (IVT). Methods: A total of 156 AIS patients who received IVT from March 2019 to March 2020 were enrolled. The modified Woodcock visual score was used to evaluate ICAC in nonenhanced head CT scans. Patients were divided into high calcification burden (HCB; score ≥3) and low calcification burden (LCB; score <3) groups. Demographic, laboratory, imaging and clinical data were compared between the two groups, and whether HCB was a prognostic factor was evaluated. Results: Compared with the LCB group, the HCB group had a higher incidence of atrial fibrillation (49.2 vs.22.1%, P < 0.001) and coronary heart disease (24.6 vs. 10.0%, P = 0.019) and higher serum homocysteine [15.31 (12.15, 17.50) vs. 14.40 (11.20, 16.20), P = 0.036] and hemoglobin A1c (6.93 ± 1.77 vs. 6.37 ± 0.74, P = 0.023) levels. Binary logistic regression analysis showed that atrial fibrillation (OR = 3.031, 95% CI: 1.312-7.006, P = 0.009) and HbA1c (OR = 1.488, 95% CI: 1.050-2.109, P = 0.026) were independent risk factors for ICAC. After adjusting for other risk factors, symptomatic-side and bilateral ICACs were independent risk factors for poor prognosis (OR = 1.969, 95% CI: 1.220-3.178, P = 0.006), (OR = 1.354, 95% CI: 1.065-1.722, P = 0.013) and mortality (OR = 4.245, 95% CI: 1.114-16.171, P = 0.034), (OR = 2.414, 95% CI = 1.152-5.060, P = 0.020) in patients with AIS who received IVT. Conclusion: ICAC is closely related to the prognosis of acute ischemic stroke after intravenous thrombolysis.

How does the pancreatic solid pseudopapillary neoplasm confuse us: Analyzing from the point view of MRI-based radiomics?

OBJECTIVES: To construct MRI-based radiomics logistic model in differentiating solid pseudopapillary neoplasm (SPN) from three differential diseases containing adenocarcinoma, neuroendocrine tumor (NET), and cystadenoma of pancreas. MATERIALS AND METHODS: A total of 21 SPNs and 140 differential diseases were enrolled. The MRI images of T1WI, T2WI, DWI, and contrast-enhanced (CE) sequences were taken to delineate the volume of interest, and the corresponding radiomics features were calculated. After the preprocess of data balance and image standardize, the data was divided into training set (6 SPNs and 42 differential diseases) and validation set (15 SPNs and 98 differential diseases) with a proportion of 7:3, randomly. Then after feature selection, four MRI-based logistic models included T1WI, T2WI, DWI, CE, and sum logistic models (Log-T1WI, Log-T2WI, Log-DWI, Log-CE, and Log-sum) were established. The receiver operation curve (ROC) was depicted to evaluate the efficacy of each model. RESULTS: To the single MRI sequence, the AUCs of Log-T1WI, Log-T2WI, Log-DWI, and Log-CE were similar. Seemingly the AUCs of Log-T2WI were slightly higher with 0. 876 (95%CI, 0.797-0.956) in the training set and 0.853 (95%CI, 0.708-0.998) in the validation set. The Log-sum of four MRI sequences displayed better differentiating efficiency, with AUCs of 0.929 (95%CI, 0.877-0.980) in the training set and 0.925 (95%CI, 0.845-1.000) in the validation set. The Log-Ra/Clin model combined clinical information and radiomics showed the highest AUC of 0.962 (95%CI, 0.919-0.985). CONCLUSIONS: MRI-based radiomics analysis helped to discern SPNs from radiologically misdiagnosed adenocarcinoma, neuroendocrine tumor, and cystadenoma of pancreas. The efficacy of single sequence logistic model was similar. The Log-sum combined four sequences and Log-Ra/Clin combined clinical information and radiomics demonstrated the better performance in distinction.

Magnetic resonance imaging-radiomics evaluation of response to chemotherapy for synchronous liver metastasis of colorectal cancer.

BACKGROUND: Synchronous liver metastasis (SLM) is an indicator of poor prognosis for colorectal cancer (CRC). Nearly 50% of CRC patients develop hepatic metastasis, with 15%-25% of them presenting with SLM. The evaluation of SLM in CRC is crucial for precise and personalized treatment. It is beneficial to detect its response to chemotherapy and choose an optimal treatment method. AIM: To construct prediction models based on magnetic resonance imaging (MRI)-radiomics and clinical parameters to evaluate the chemotherapy response in SLM of CRC. METHODS: A total of 102 CRC patients with 223 SLM lesions were identified and divided into disease response (DR) and disease non-response (non-DR) to chemotherapy. After standardizing the MRI images, the volume of interest was delineated and radiomics features were calculated. The MRI-radiomics logistic model was constructed after methods of variance/Mann-Whitney U test, correlation analysis, and least absolute shrinkage and selection operator in feature selecting. The radiomics score was calculated. The receiver operating characteristics curves by the DeLong test were analyzed with MedCalc software to compare the validity of all models. Additionally, the area under curves (AUCs) of DWI, T2WI, and portal phase of contrast-enhanced sequences radiomics model (Ra-DWI, Ra-T2WI, and Ra-portal phase of contrast-enhanced sequences) were calculated. The radiomics-clinical nomogram was generated by combining radiomics features and clinical characteristics of CA19-9 and clinical N staging. RESULTS: The AUCs of the MRI-radiomics model were 0.733 and 0.753 for the training (156 lesions with 68 non-DR and 88 DR) and the validation (67 lesions with 29 non-DR and 38 DR) set, respectively. Additionally, the AUCs of the training and the validation set of Ra-DWI were higher than those of Ra-T2WI and Ra-portal phase of contrast-enhanced sequences (training set: 0.652 vs 0.628 and 0.633, validation set: 0.661 vs 0.575 and 0.543). After chemotherapy, the top four of twelve delta-radiomics features of Ra-DWI in the DR group belonged to gray-level run-length matrices radiomics parameters. The radiomics-clinical nomogram containing radiomics score, CA19-9, and clinical N staging was built. This radiomics-clinical nomogram can effectively discriminate the patients with DR from non-DR with a higher AUC of 0.809 (95% confidence interval: 0.751-0.858). CONCLUSION: MRI-radiomics is conducive to predict chemotherapeutic response in SLM patients of CRC. The radiomics-clinical nomogram, involving radiomics score, CA19-9, and clinical N staging is more effective in predicting chemotherapeutic response.

Social cognition in multiple sclerosis and its subtypes: A meta-analysis.

BACKGROUND: Multiple sclerosis (MS) is an immune-mediated demyelinating disease that disrupts several social cognitive abilities, including the theory of mind (ToM) and facial emotion recognition (FER). It is unclear how specific ToM subcomponents, including cognitive and affective ToM, are affected in patients with MS and the social cognitive abilities in MS subtypes. METHODS: A search of PubMed, Web of Science, and Embase databases was conducted until June 2020. Effect sizes were calculated using Hedges g with a random-effects model. RESULTS: A total of 45 studies were included. Relative to health controls (HCs), patients with MS and its subtypes (including relapsing-remitting MS [RRMS] and progressive MS) exhibited impairments in ToM (g = -0.77, g = -0.70, g = -0.75, respectively), cognitive ToM (g = -0.72, g = -0.83, g = -0.73, respectively), affective ToM (g = -0.84, g = -0.63, g = -0. 50, respectively), and FER (g = -0.62, g = -0.53, g = -1.07, respectively). In addition, there was no difference between progressive primary MS and secondary progressive MS in overall ToM, cognitive ToM, affective ToM, and FER. Compared to patients with RRMS, patients with progressive MS showed no difference in overall ToM, cognitive ToM, and affective ToM but had more serious defects in FER (g = -0.57). CONCLUSIONS: These quantitative results indicate that patients with MS and its subtypes have a differential impairment of the core aspects of social cognitive processing (including ToM and FER), which may help develop the structured social cognitive interventions in MS.

Empathy and Theory of Mind in Multiple Sclerosis: A Meta-Analysis.

Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the central nervous system. Studies have shown that MS disrupts several social cognitive abilities [including empathy and theory of mind (ToM)]. Overall ToM deficits in MS are well documented, but how the specific ToM subcomponents and empathic capacity are affected remains unclear. For this meta-analysis, we searched PubMed, Web of Science, and Embase from inception to July 2020. Effect sizes were calculated using Hedges g with a random-effects model. Thirty-three studies were included. Relative to healthy controls (HCs), patients with MS were moderately impaired in overall empathy (g = -0.67), overall ToM (g = -74), cognitive ToM (g = -0.72), and the overlapping domains of cognitive empathy/affective ToM (g = -0.79); no group differences were identified for affective empathy (g = -0.19). Compared with HCs, patients with relapsing-remitting MS (RRMS) and progressive MS were impaired in overall empathy, overall ToM, cognitive ToM, and cognitive empathy/affective ToM, without significant RRMS-progressive MS differences in impairment degree. We conducted the first meta-analytic review investigating the empathy and ToM functioning patterns in patients with MS and examined the overlapping and distinct subcomponents of these constructs. The findings suggest differential impairment of the core aspects of social cognitive processing in patients with MS, which may importantly inform the development of structured social cognitive MS interventions.

Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma via Multi-Parametric MRI Radiomics.

OBJECTIVES: To systematically evaluate and compare the predictive capability for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients based on radiomics from multi-parametric MRI (mp-MRI) including six sequences when used individually or combined, and to establish and validate the optimal combined model. METHODS: A total of 195 patients confirmed HCC were divided into training (n = 136) and validation (n = 59) datasets. All volumes of interest of tumors were respectively segmented on T2-weighted imaging, diffusion-weighted imaging, apparent diffusion coefficient, artery phase, portal venous phase, and delay phase sequences, from which quantitative radiomics features were extracted and analyzed individually or combined. Multivariate logistic regression analyses were undertaken to construct clinical model, respective single-sequence radiomics models, fusion radiomics models based on different sequences and combined model. The accuracy, sensitivity, specificity and area under the receiver operating characteristic curve (AUC) were calculated to evaluate the performance of different models. RESULTS: Among nine radiomics models, the model from all sequences performed best with AUCs 0.889 and 0.822 in the training and validation datasets, respectively. The combined model incorporating radiomics from all sequences and effective clinical features achieved satisfactory preoperative prediction of MVI with AUCs 0.901 and 0.840, respectively, and could identify the higher risk population of MVI (P < 0.001). The Delong test manifested significant differences with P < 0.001 in the training dataset and P = 0.005 in the validation dataset between the combined model and clinical model. CONCLUSIONS: The combined model can preoperatively and noninvasively predict MVI in HCC patients and may act as a usefully clinical tool to guide subsequent individualized treatment.

Grey matter alterations in restless legs syndrome: A coordinate-based meta-analysis.

Brain structural abnormalities in idiopathic restless legs syndrome have long been debated. Voxel-based morphometry is an objective structural magnetic resonance imaging technique to investigate regional grey matter volume or density differences between groups. In the last decade, voxel-based morphometry studies have exhibited inconsistent and conflicting findings regarding the presence and localization of brain grey matter alterations in restless legs syndrome. We therefore conducted a coordinate-based meta-analysis to quantitatively examine whether there were consistent grey matter findings in restless legs syndrome using the latest algorithms, seed-based d mapping with permutation of subject images. We included 12 voxel-based morphometry studies (13 datasets, 375 patients and 385 healthy controls). Our coordinate-based meta-analysis did not identify evidence of consistent grey matter alterations in restless legs syndrome. Grey matter alterations via voxel-based morphometry analysis are not therefore recommended to be used as a reliable surrogate neuroimaging marker for restless legs syndrome. This lack of consistency may be attributed to differences in sample size, genetics, gender distribution and age at onset, clinical heterogeneity (clinical course, anatomical distribution of symptoms, disease severity, disease duration, abnormal sensory profiles and comorbidity), and variations in imaging acquisition, data processing and statistical strategies. Longitudinal studies with multimodal neuroimaging techniques are needed to determine whether structural changes are dynamic and secondary to functional abnormalities.